Spatio-temporal Analysis through NDVI, NDBI, and SAVI Using Landsat 8/9 OLI

Yerik Afrianto Singgalen

doi:10.47065/josyc.v5i4.5735

Yerik Afrianto Singgalen * Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/josyc.v5i4.5735

Keywords: Remote Sensing; Spatio-temporal Analysis; NDVI; NDBI; SAVI

Abstract

This research underscores the significant role of remote sensing and spatio-temporal analysis in promoting sustainable tourism development on Kakara Island, North Halmahera. Applying NDVI, NDBI, and SAVI models provided valuable insights into vegetation health, urban expansion, and soil-adjusted indices from 2013 to 2024. NDBI values in 2013, 2018, and 2024 revealed changes in urban development with minimum values of -0.8837597, -0.8867515, and -0.7182528, respectively. NDVI values indicated improvements in vegetation health, with mid values increasing from 0.3804683 in 2013 to 0.8090699 in 2024. Similarly, SAVI values demonstrated better vegetation density, with maximum values rising from 0.3782764 in 2013 to 0.6022941 in 2024. These models effectively monitored environmental changes and informed sustainable land management practices. As tourism on Kakara Island grows, with visitor numbers increasing by 25% annually, a balanced approach is essential to preserve its natural and cultural heritage. Integrating remote sensing and spatio-temporal analysis is crucial for identifying areas under environmental stress and implementing sustainable practices to mitigate negative impacts. Future research should include additional models, such as the Enhanced Vegetation Index (EVI) and Normalized Burn Ratio (NBR), and integrate socio-economic data with environmental datasets for a more comprehensive understanding. This approach will foster sustainable development that benefits both the environment and the local community, ensuring the long-term resilience and viability of Kakara Island's tourism industry.

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